Tag Archives: medians

Under the implementation of the Affordable Care Act promulgated by the Obama administration, the federal government publishes a list each June 1 of health insurers seeking to increase their premiums by over 10% from one year to the next. Today, the Obama administration released their data for 2016. There are a lot of insurance plans and a lot of very high requested increases on the list.

My examination of the data this afternoon shows 661 insurance plans in which a rate increase of over 10% is being requested. And the increases requested by these insurers is often way over 10%. The median increase requested by insurers on the list it varies from a low of 12% in New Jersey to 59% in New Mexico. Median means half the numbers are below the median and half are above the median. Thus a median increase of 32% in Pennsylvania means that half the insurers there on the list are asking for more than a 32% increase in premiums.

An aggregation of the data is also revealing. If one looks at the median increase in each state, the “median of the median” is 19%. Half of the states are seeing median increases of less than 19% and half are seeing median increases of more than 19%.

Most of the analyses of this data thus far have looked at particular states and found them troubling. Taken as a whole, however, the widespread significant increases should be disturbing to those who were confident that the Affordable Care Act would continue to result in low premiums.

Moreover, the median figures cited above are by no means the maximum increases requested by insurers. Let us start with some heavily populated states and take a look at some representative high increase requests. In Texas, Time Insurance is requesting a 65% increase. In Florida, Time Insurance is asking for 63% on one of its products; the better known UnitedHealthcare is asking for 31%. In Illinois, Blue Cross is asking for a 38% increase on one of its plans; Coventry, also a good sized player, is asking for 34% on another. In Pennsylvania, a Geisinger plan is asking for 58%; Geisinger is a significant player in that state. The list goes on and on.

The table

The table below shows the data I was able to mine from healthcare.gov on the rate increases.

State

Number of plans reporting

Median Rate Increase (Conditional on Rate Increase > 10%)

Rank

Alabama

14

24

13

Alaska

13

24

14

Arizona

24

20

17

Arkansas

3

21

16

California

0

N/A

Colorado

0

N/A

Delaware

26

16

28

District of Columbia

8

14

38

Florida

13

18

25

Georgia

27

16

29

Hawaii

6

18

22

Idaho

57

19

20

Illinois

16

15

31

Iowa

30

25

11

Kansas

15

35

3

Kentucky

0

N/A

Louisiana

15

18

26

Maine

0

N/A

Maryland

8

30

6

Massachusetts

0

N/A

Michigan

12

15

33

Minnesota

0

N/A

Mississippi

6

26

10

Missouri

13

16

30

Montana

12

34

4

Nebraska

12

15

32

Nevada

25

14

36

New Hampshire

11

44

2

New Jersey

7

12

40

New Mexico

3

59

1

New York

0

N/A

North Carolina

17

26

8

North Dakota

3

18

23

Ohio

15

14

34

Oklahoma

8

28

7

Oregon

23

20

18

Pennsylvania

51

32

5

Rhode Island

0

N/A

South Carolina

10

24

12

South Dakota

18

17

27

Tennessee

12

14

35

Texas

22

26

9

Utah

31

19

21

Vermont

0

N/A

Virginia

19

14

37

Washington

24

13

39

West Virginia

14

19

19

Wisconsin

12

18

24

Wyoming

6

23

15

Caveats

All of that said, the figures should not be misinterpreted. The following caveats must be considered.

1. The data only lists those insurers that requested an increase of more than 10%. There are many plans that requested increases less than that amount. So it is incorrect to say that the average or median increase in insurance prices is going to be 19%. If a lot of big insurers are requesting increases less than 10%, the average increase will be less than 19%. On the other hand, if the big insurers are over 19% and it is mostly small insurers that are submitting rate increase requests of under 10%, then the 19% figure is too low.

2. The data is not weighted by the number of policies sold by an insurer. With all respect to small insurers (and small states), in the grand scheme of things it does not matter much if a small insurer in a small state is raising its rates 40%. Of course it will affect the people involved, but it is not a good bellwether of the performance of the ACA. On the other hand, if a big insurer in a big state, like Scott & White in Texas, is requesting increases (as is the case) of 32%, that is a very big deal. Until we have an estimate of the number of policies sold by each insurer, a secret that seems to be more tightly guarded than many diplomatic communications, it is hard to know perfectly what the numbers in the list actually mean.

3. The data for some important states is missing. We have no data for New York and California, for example, and no data from about seven other states. Does that mean that there are no insurers there requesting more than a 10% increase, that the data is just delayed, or is there another explanation? Until this mystery is resolved, it’s hard to know fully what the numbers published today imply.

4. Ask does not equal get. All we have right now are the rate increases requested by insurers. There now follows a review process in which the reasonableness of the rate increases are examined. If the federal government or, in some instances, the states find the rate increases unreasonable, then they do not go into effect. Of course, insurers who see their rate increases denied, may decline to sell the policies, which results in less competition and leaves many insureds without any continuity in coverage. Yes, it is possible that some insurers are bluffing and requesting pie in the sky. The risk in calling that bluff by denying or modifying a rate increase is that the insurer may pull out.

5. I basically did this analysis by hand because CMS has not released the data in a form (such as Excel, CSV, JSON or others) that would facilitate machine analysis. I tried to do the work carefully, but I am an imperfect human. I am doubtful, however, that any errors materially affect the conclusions here.